New curve-tracing algorithm based on a minimum-spanning-tree model and regularized fuzzy clustering

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

View graph of relations

Author(s)

Detail(s)

Original languageEnglish
Article number17201
Journal / PublicationOptical Engineering
Volume45
Issue number1
Publication statusPublished - Jan 2006

Abstract

Extracting a smooth curve from unordered data has many applications to image analysis. However, many reported methods assume either that the shape of the input data is known a priori or that the boundary of the data is clearly defined. We present a method that can handle several types of data sets. The main idea of the method is to extract a generalized curve, which passes through the data set. The proposed method is able to extract a smooth curve from complicated unordered pattern data and without any prior knowledge of the shape of the input data. Experimental results show that our method can produce good, results for many data sets including handwritten Chinese characters. © 2006 Society of Photo-Optical Instrumentation Engineers.

Research Area(s)

  • Eikonal equation, Fuzzy C-means (FCM) clustering algorithm, Fuzzy curve-tracing (FCT) algorithm, Handwritten Chinese characters, Minimum spanning tree (MST), Prim's algorithm, Skeletonization, Thinning